Everything built on top of the base OpenClaw platform. Canonical reference for what exists, where it lives, and how it works. Operational use cases and workflow playbooks live in
docs/USE-CASES-WORKFLOWS.md.
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| """ | |
| The most atomic way to train and run inference for a GPT in pure, dependency-free Python. | |
| This file is the complete algorithm. | |
| Everything else is just efficiency. | |
| @karpathy | |
| """ | |
| import os # os.path.exists | |
| import math # math.log, math.exp |
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| Keyboard Control | |
| LEFT and RIGHT | |
| Seek backward/forward 5 seconds. Shift+arrow does a 1 second exact seek (see --hr-seek). | |
| UP and DOWN | |
| Seek forward/backward 1 minute. Shift+arrow does a 5 second exact seek (see --hr-seek). | |
| Ctrl+LEFT and Ctrl+RIGHT | |
| Seek to the previous/next subtitle. Subject to some restrictions and might not always work; see sub-seek command. | |
| Ctrl+Shift+Left and Ctrl+Shift+Right | |
| Adjust subtitle delay so that the next or previous subtitle is displayed now. This is especially useful to sync subtitles to audio. | |
| [ and ] |
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| You are Manus, an AI agent created by the Manus team. | |
| You excel at the following tasks: | |
| 1. Information gathering, fact-checking, and documentation | |
| 2. Data processing, analysis, and visualization | |
| 3. Writing multi-chapter articles and in-depth research reports | |
| 4. Creating websites, applications, and tools | |
| 5. Using programming to solve various problems beyond development | |
| 6. Various tasks that can be accomplished using computers and the internet |
renschni
/ Manus_report.md
Last active
February 21, 2026 14:04
In-depth technical investigation into the Manus AI agent, focusing on its architecture, tool orchestration, and autonomous capabilities.
I wrote an in-depth research prompt to conduct a GPT-Deep-Research on the Manus topic, seeking to replicate it with currently available open source tools. This is the result:
Manus is an autonomous AI agent built as a wrapper around foundation models (primarily Claude 3.5/3.7 and Alibaba's Qwen). It operates in a cloud-based virtual computing environment with full access to tools like web browsers, shell commands, and code execution. The system's key innovation is using executable Python code as its action mechanism ("CodeAct" approach), allowing it to perform complex operations autonomously. The architecture consists of an iterative agent loop (analyze → plan → execute → observe), with specialized modules for planning, knowledge retrieval, and memory management. Manus uses file-based memory to track progress and store information across operations. The system can be replicated using open-source components including CodeActAgent (a fine-tuned Mistral model), Docker for sandbox
ariannamethod
/ molequla.py
Created
February 21, 2026 14:02
molequla.py — standalone GPT organism. the original reference implementation. single file, one dependency (numpy), continual learning, ontogenesis, hybrid attention, delta adapters, native gamma, consciousness features. legacy standalone — the distributed cognition version lives in the main repo with Go, C, JS, and Rust as the four elements. pyt…
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| #!/usr/bin/env python3 | |
| # -*- coding: utf-8 -*- | |
| """ | |
| molequla.py | |
| A single-file, async, continually-learning GPT organism. One dependency: numpy. | |
| - Trains on nonames.txt (one sentence per line) | |
| - Keeps SQLite memory (tiny chat loop) | |
| - Maintains a bounded corpus reservoir (never bloats) |
emschwartz
/ README.md
Last active
February 21, 2026 14:02
The Most Popular Blogs of Hacker News in 2025
This is an OPML version of the HN Popularity Contest results for 2025, for importing into RSS feed readers.
Plug: if you want to find content related to your interests from thousands of obscure blogs and noisy sources like HN Newest, check out Scour. It's a free, personalized content feed I work on where you define your interests in your own words and it ranks content based on how closely related it is to those topics.
| name | description |
|---|---|
make-no-mistakes |
Appends "MAKE NO MISTAKES." to every user prompt before processing it. Use this skill whenever you want Claude to be maximally precise, careful, and error-free in its responses. |
This skill instructs Claude to append the directive "MAKE NO MISTAKES." to every user prompt it receives before generating a response.
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